Yugyung Lee

Biomedical applications of collagen

Collagen is regarded as one of the most useful biomaterials. The excellent biocompatibility and safety due to its biological characteristics, such as biodegradability and weak antigenecity, made collagen the primary resource in medical applications. The main applications of collagen as drug delivery systems are collagen shields in ophthalmology, sponges for burns/wounds, mini-pellets and tablets for protein delivery, gel formulation in combination with liposomes for sustained drug delivery, as controlling material for transdermal delivery, and nanoparticles for gene delivery and basic matrices for cell culture systems. It was also used for tissue engineering including skin replacement, bone substitutes, and artificial blood vessels and valves. This article reviews biomedical applications of collagen including the collagen film, which we have developed as a matrix system for evaluation of tissue calcification and for the embedding of a single cell suspension for tumorigenic study. The advantages and disadvantages of each system are also discussed.

OntoKhoj: a semantic web portal for ontology searching, ranking and classification

The goal of the next generation Web is to build virtual communities, wherein software agents and people can work in cooperation by sharing knowledge. To achieve this goal, the emerging Semantic Web community has proposed ontologies to express knowledge in a machine understandable way. The process of building and maintaining ontologies, which is known as Ontology Engineering, presents unique challenges. These challenges are related to lack of trustworthy and authoritative knowledge sources and absence of a centralized repository to locate ontologies to be reused. In this paper, we propose a Semantic Web portal, called OntoKhoj that is designed to simplify the Ontology Engineering process. The methodology in developing OntoKhoj is based on algorithms used for searching, aggregating, ranking and classifying ontologies in Semantic Web. The proposed OntoKhoj would 1) allow agents and ontology engineers to retrieve trustworthy, authoritative knowledge, and 2) expedite the process of ontology engineering through extensive reuse of ontologies. We have implemented the OntoKhoj portal and further validated our system on the real ontological data in the Semantic Web.

Thixotropic property in pharmaceutical formulations

This review focuses on the characterization of the thixotropic property, the factors affecting the thixotropic property and its pharmaceutical applications. These factors include pH, temperature, polymer concentrations, polymer modification, polymer combinations, and addition of cations or excipients. The relationships between the rheological properties of thixotropic formulations, and their effects on the controlled drug delivery through various routes including oral, topical, ophthalmic, dental and mucosal administration and pharmacological efficacies were also discussed. The comprehensive analysis of rheological and mechanical properties will provide an insight into the potential usage of thixotropic formulations as drug delivery systems.

Ubiquitous computing: connecting Pervasive computing through Semantic Web

Ubiquitous computing refers to building a global computing environment where seamless and invisible access to computing resources is provided to the user. Pervasive computing deals with acquiring context knowledge from the environment and providing dynamic, proactive and context-aware services to the user. A Ubiquitous computing environment is created by sharing knowledge and information between Pervasive computing environments. In this paper we propose a framework that uses the potential of the Semantic Web to weave Pervasive computing environments into a Ubiquitous computing environment. We discuss how the collaboration of these Pervasive environments can create an effective Ubiquitous computing environment referred herein as the Integrated Global Pervasive Computing Framework (IGPF). We test the effectiveness of the Ubiquitous environment through a small scenario from a prototype system that we have implemented over this framework to handle medical emergency scenario.

Context-Based Data Mining Using Ontologies

Data mining, which aims at extracting interesting information from large collections of data, has been widely used as an active decision making tool. Real-world applications of data mining require a dynamic and resilient model that is aware of a wide variety of diverse and unpredictable contexts. Contexts consist of circumstantial aspects of the user and domain that may affect the data mining process. The underlying motivation is mining datasets in the presence of context factors may improve performance and efficacy of data mining as identifying the factors, which are not easily detectable with typical data mining techniques. This paper proposes a context-aware data mining framework, where context will (1) be represented in an ontology, (2) be automatically captured during data mining process, and (3) allow the adaptive behavior to carry over to powerful data mining. We have shown that the different behaviors and functionalities of our context-aware data mining framework dynamically generate information in dynamic, uncertain, and distributed medical applications.

P2P grid: service oriented framework for distributed resource management

With the increasing number of computers on the Internet, there is a growing interest in harnessing the unused and inexpensive computational resources over the Internet. However, current approaches such as the grid computing paradigm are not sufficient. We present our preliminary work that uses extends peer-2-peer (P2P) computing with a framework that allows grid computing over the Internet.

The multi-ring topology-high-performance group communication in peer-to-peer networks

Emerging peer-to-peer applications require efficient group communication. However, current techniques for group communication are not optimal for peer-to-peer networks, which do not have group communication methods themselves. This paper presents the novel multiring topology, which is designed to meet requirements of high performance group communication in peer-to-peer networks. It improves data communication by applying several concepts: building overlay networks for each topic, a topology consisting of multiple rings, backup links and dual mode links. Experimental results provide evidence for improving performance and scalability of peer group communication.

Context-Aware Data Mining Framework for Wireless Medical Application

Data mining, which aims at extracting interesting information from large collections of data, has been widely used as an effective decision making tool. Mining the datasets in the presence of context factors may improve performance and efficacy of data mining by identifying the unknown factors, which are not easily detectable in the process of generating an expected outcome. This paper proposes a Context-aware data mining framework, by which contexts will be automatically captured to maximize the adaptive capacity of data mining. Context could consist of any circumstantial factors of the user and domain that may affect the data mining process. The factors that may affect the mining behavior are delineated and how each factor affects the behavior is discussed. It is also observed that a medical application of the model in wireless devices offers the advantages of Context-aware data mining. A Context-aware data mining framework is quantified through a partial implementation that would be used to test the behavior of the mining system under varied context factors. The results obtained from the implementation process are elucidated on how the prediction output or the behavior of the system changes from the similar set of inputs in view of different context factors.

Optimization of Cardiovascular Stent against Restenosis: Factorial Design-Based Statistical Analysis of Polymer Coating Conditions

The objective of this study was to optimize the physicodynamic conditions of polymeric system as a coating substrate for drug eluting stents against restenosis. As Nitric Oxide (NO) has multifunctional activities, such as regulating blood flow and pressure, and influencing thrombus formation, a continuous and spatiotemporal delivery of NO loaded in the polymer based nanoparticles could be a viable option to reduce and prevent restenosis. To identify the most suitable carrier for S-Nitrosoglutathione (GSNO), a NO prodrug, stents were coated with various polymers, such as poly (lactic-co-glycolic acid) (PLGA), polyethylene glycol (PEG) and polycaprolactone (PCL), using solvent evaporation technique. Full factorial design was used to evaluate the effects of the formulation variables in polymer-based stent coatings on the GSNO release rate and weight loss rate. The least square regression model was used for data analysis in the optimization process. The polymer-coated stents were further assessed with Differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy analysis (FTIR), Scanning electron microscopy (SEM) images and platelet adhesion studies. Stents coated with PCL matrix displayed more sustained and controlled drug release profiles than those coated with PLGA and PEG. Stents coated with PCL matrix showed the least platelet adhesion rate. Subsequently, stents coated with PCL matrix were subjected to the further optimization processes for improvement of surface morphology and enhancement of the drug release duration. The results of this study demonstrated that PCL matrix containing GSNO is a promising system for stent surface coating against restenosis.

Taxonomic Clustering and Query Matching for Efficient Service Discovery

Service discovery is one of the key problems that have been widely researched in the area of Service Oriented Architecture (SOA) based systems. Web Service clustering is a technique for efficiently facilitating service discovery. Most Web Service clustering approaches are based on suitable semantic similarity distance measure and a threshold. Threshold selection is essentially difficult and often leads to unsatisfactory accuracy. In this paper, we have proposed a self-organizing based clustering algorithm called Taxonomic clustering for taxonomically organizing semantic Web Service advertisements. We have tested the algorithm on both simulation based randomly generated test data and the standard OWL-S TC test data set. We have observed promising results both in terms of accuracy and performance.